Targeted emission reductions in the Boston metropolitan region: assessing health and equity outcomes across vehicle classes and source regions

Abstract Background: Vehicle electrification is a key component of many climate action plans, however, its benefits and impacts vary by implementation location and strategy. Given limited governmental resources, understanding how targeting emission reductions in specific sources and regions affects overall outcomes is important for effective planning.
Objective: This study examines how place-specific emission reductions in different vehicle classes across regions of the Boston metropolitan area influence pollutant exposures, health benefits, and related inequities. 
Methods: Using the Community Multiscale Air Quality model, we analyzed PM2.5, NO2, and O3 concentration sensitivities to on-road vehicle emissions at 1.33 km x 1.33 km resolution. We integrated the air pollutant estimates with area-level health data to assess the benefits and impacts of changing on-road vehicle emissions from five vehicle classes (light-duty autos; light-duty, medium-duty, and heavy-duty trucks; and buses) across six inner core and suburban source regions within the metropolitan area. We modeled emission reduction scenarios to evaluate effects on all-cause mortality, adult asthma emergency department visits, and health inequities among racial and ethnic groups.
Results: Our analysis revealed tradeoffs between total health benefits and reductions in health inequities. Emission reductions from larger suburban fleets led to greater overall health benefits but primarily benefited non-Hispanic White communities, which, on average, had lower exposure and health burdens at baseline. Targeting heavy-duty trucks in inner core regions maximized health benefits and reduced inequities when considered per vehicle. NO2 was identified as the primary driver of health impacts and inequities.
Discussion: This study provides policymakers with insights for assessing climate action plans and vehicle electrification policies. We highlight the importance of considering multiple pollutants and using high-resolution health data. This framework helps evaluate strategies balancing overall health benefits with reductions in health inequities, offering valuable guidance for resource-constrained environments.